On 4/18/07, [EMAIL PROTECTED]
<[EMAIL PROTECTED]> wrote:
> ------------------------------
>
> Message: 5
> Date: Wed, 18 Apr 2007 09:11:32 -0700
> From: Christopher Barker <[EMAIL PROTECTED]>
> Subject: Re: [Numpy-discussion] Help using numPy to create a very
> large multi dimensional array
> To: Discussion of Numerical Python <numpy-discussion@scipy.org>
> Message-ID: <[EMAIL PROTECTED]>
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
>
> Bruno Santos wrote:
> > Finally I was able to read the data, by using the command you sair with
> > some small changes:
> > matrix = numpy.array([[float(x) for x in line.split()[1:]] for line in
> > vecfile])
>
> it doesn't sound like you're concerned about the speed of reading the
> files, but you can still use fromfile() or maybe fromstring() to do
> this. You just need to read past the text part first, then process it.
>
> using fromstring:
>
> matrix = numpy.vstack([numpy.fromstring(line.split(" ", 1)[1], sep=" ")
> for line in vecfile])
>
> or something like that.
>
> -Chris
I would strongly recommend pylab.load. It handles comments, selects
columns, and is legible.
Examples from the docstring:
t,y = load('test.dat', unpack=True) # for two column data
x,y,z = load('somefile.dat', usecols=(3,5,7), unpack=True)
A more advanced example from examples/load_converter.py:
dates, closes = load(
'data/msft.csv', delimiter=',',
converters={0:datestr2num}, skiprows=1, usecols=(0,2),
unpack=True)
Devs, is there any possibility of moving/copying pylab.load to numpy?
I don't see anything in the source that requires the rest of
matplotlib. Among convenience functions, I think that this function
ranks pretty highly in convenience.
Take care,
Nick
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